Multi-variable state closed-loop control for a steam generator of a thermal power plant

Abstract

A device for closed-loop control of a plurality of state variables of a steam generator of a thermal power plant is provided. In order to achieve stable and exact closed-loop control of the plurality of state variables, a multi-variable control / controller controls the plurality of state variables and uses a linear quadratic controller for this multi-variable control / controller.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application claims priority to DE 102014205629.2 having a filing date of Mar. 26, 2014 the entire contents of which are hereby incorporated by reference.FIELD OF TECHNOLOGY[0002]The following relates to a method and a device for controlling a plurality of state variables of a steam generator of a thermal power plant.BACKGROUND[0003]Thermal power plants are widely known, for example from http: / / de.wikipedia.org / wiki / Dampfkraftwerk (retrievable on Mar. 21, 2014). A thermal power plant is a type of a power plant for generating power from fossil fuels, in which thermal energy of steam is converted into kinetic energy, usually in a multi-part steam turbine, and, furthermore, converted into electrical energy in a generator. In such a thermal power plant, a fuel, e.g. coal, is burned in a combustion chamber, releasing heat.[0004]The heat released thereby is taken up by a steam generator, i.e. a power plant boiler, consisting of an evaporato...

AI Technical Summary

Benefits of technology

This patent is about a way to control a steam generator in a power plant using a closed-loop system. The new system solves problems of previous methods by accurately and stably controlling multiple variables in the steam generator. It is also cost-effective and easy to implement.

Problems solved by technology

However, the LQG method employed—according to EP 2 244 011 A1—relates to a linear control problem, whereas the injection rate of mass flow as a manipulated variable of the (single variable) state control acts on the controlled variable temperature in a nonlinear manner.

However, since the plurality of (but single) control loops of the individual (single variable) state controls—like, for example, in the thermal power plant—are coupled to one another by means of a common controlled system, such as the steam generator, there necessarily is mutual influencing of the individual controllers.

The parameterization requires much (time) outlay and is correspondingly expensive.

Here, i.e. in the case of these known multi-variable controllers, it has proven disadvantageous that in general transfer functions between the (plurality of) input variables and the plurality of output variables and, possibly, the (plurality of) disturbance variables can in most cases only be established by complicated tests.

Moreover, nonlinearities or load dependencies can only be taken into account here with difficulty.

Here, large values mean very noisy measurements, and so trust is more likely to be put into prediction by the model.

However, the interplay is complex such that, for reasons of simple parameterizability, tuning by way of the factor can be preferred.

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